Here a novel region of interest analysis protocol based on sorting best-fit ellipses assigned to regions of positive signal within two-dimensional time lapse image sequences is demonstrated. This algorithm may enable investigators to comprehensively analyze physiological Ca2+ signals with minimal user input and bias.
This protocol describes the reprogramming of primary amniotic fluid and membrane mesenchymal stem cells into induced pluripotent stem cells using a non-integrating episomal approach in fully chemically defined conditions. Procedures of extraction, culture, reprogramming, and characterization of the resulting induced pluripotent stem cells by stringent methods are detailed.
Simple methods are described for demonstrating the production of cytotoxic amyloids following infection of pulmonary endothelium by Pseudomonas aeruginosa.
Spectral imaging has become a reliable solution for identification and separation of multiple fluorescence signals in a single sample and can readily distinguish signals of interest from background or autofluorescence. Excitation-scanning hyperspectral imaging improves on this technique by decreasing the necessary image acquisition time while simultaneously increasing the signal-to-noise ratio.
Due to inherent low signal-to-noise ratio (SNR) of Fӧrster resonance energy transfer (FRET) based sensors, measurement of cAMP signals has been challenging, especially in three spatial dimensions. Here, we describe a hyperspectral FRET imaging and analysis methodology that allows measurement of cAMP distribution in three spatial dimensions.
The Integrative Toolkit to Analyze Cellular Signals (iTACS) platform automates the process of simultaneously measuring a wide variety of chemical and mechanical signals in adherent cells. iTACS is designed to facilitate community-driven development and enable researchers to use all platform features regardless of their educational background.
Ex vivo lungs are useful for a variety of experiments to collect physiological data while excluding the confounding variables of in vivo experiments. Commercial setups are often expensive and limited in the types of data they can collect. We describe a method for building a fully modular setup, adaptable for various study designs.
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